Oskar Wysocki

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 16

Top Topics

Learning Models

Evaluation Campaigns

Using Artificial Neural Networks

Top Venues

Comput. Linguistics

Publications

Oskar Wysocki, Magdalena Wysocka, Danilo Carvalho, Alex Teodor Bogatu, Danilo Miranda Gusicuma, Maxime Delmas, Harriet Unsworth, André Freitas
An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery. CoRR (2024)
Oskar Wysocki, Zili Zhou, Paul O'Regan, Deborah Ferreira, Magdalena Wysocka, Dónal Landers, André Freitas
Transformers and the Representation of Biomedical Background Knowledge. Comput. Linguistics 49 (1) (2023)
Magdalena Wysocka, Oskar Wysocki, Marie Zufferey, Dónal Landers, André Freitas
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data. BMC Bioinform. 24 (1) (2023)
Magdalena Wysocka, Oskar Wysocki, Maxime Delmas, Vincent Mutel, André Freitas
Large Language Models, scientific knowledge and factuality: A systematic analysis in antibiotic discovery. CoRR (2023)
Oskar Wysocki, Jessica Katharine Davies, Markel Vigo, Anne Caroline Armstrong, Dónal Landers, Rebecca Lee, André Freitas
Assessing the communication gap between AI models and healthcare professionals: Explainability, utility and trust in AI-driven clinical decision-making. Artif. Intell. 316 (2023)
Alex Bogatu, Magdalena Wysocka, Oskar Wysocki, Holly Butterworth, Manon Pillai, Jennifer Allison, Dónal Landers, Elaine Kilgour, Fiona Thistlethwaite, André Freitas
Meta-analysis informed machine learning: Supporting cytokine storm detection during CAR-T cell Therapy. J. Biomed. Informatics 142 (2023)
Hanadi Mardah, Oskar Wysocki, Markel Vigo, André Freitas
On the Visualisation of Argumentation Graphs to Support Text Interpretation. CoRR (2023)
Magdalena Wysocka, Oskar Wysocki, Marie Zufferey, Dónal Landers, André Freitas
Biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data. CoRR (2022)
Oskar Wysocki, Zili Zhou, Paul O'Regan, Deborah Ferreira, Magdalena Wysocka, Donal Landers, André Freitas
Transformers and the representation of biomedical background knowledge. CoRR (2022)
Oskar Wysocki, Jessica Katharine Davies, Markel Vigo, Anne Caroline Armstrong, Dónal Landers, Rebecca Lee, André Freitas
Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making. CoRR (2022)
Alex Bogatu, Magdalena Wysocka, Oskar Wysocki, Holly Butterworth, Donal Landers, Elaine Kilgour, André Freitas
Metareview-informed Explainable Cytokine Storm Detection during CAR-T cell Therapy. CoRR (2022)
Oskar Wysocki, Malina Florea, Dónal Landers, André Freitas
What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP. Eval4NLP (2021)
Oskar Wysocki, Malina Florea, Donal Landers, André Freitas
Architectures of Meaning, A Systematic Corpus Analysis of NLP Systems. CoRR (2021)
Oskar Wysocki, Malina Florea, André Freitas
What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP. CoRR (2020)
Oskar Wysocki, Lipika Deka, David Elizondo
Heavy duty vehicle fuel consumption modeling using artificial neural networks. ICAC (2019)
Oskar Wysocki, Lipika Deka, David A. Elizondo, Jacek Kropiwnicki, Jacek Czyzewicz
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks. IWANN (1) (2019)